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The Inworld Realtime API uses an OpenAI Realtime API-compatible event system to facilitate voice experiences. This guide summarizes the key building blocks documented in the API reference (API reference).

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Configure a Session

Every connection starts with session.created. Immediately follow with session.update to configure your session. Here you can set:
  • modelId — LLM provider and model (e.g. openai/gpt-4.1-nano) or router (e.g. inworld/latency-optimizer-ab-test)
  • instructions
  • output_modalities (["audio", "text"], ["audio"], or ["text"])
  • Audio input and output configuration — voice, TTS model, PCM format, speed
  • max_output_tokens ("inf" or a numeric ceiling)
  • tools (function definitions) and tool_choice settings
Partial updates are supported, so you can adjust the LLM, voice, TTS model, temperature, or tool lists mid-session without rebuilding the socket. 
ws.send(JSON.stringify({
  type: 'session.update',
  session: {
    type: 'realtime',
    modelId: 'openai/gpt-4o-mini',
    instructions: 'You are a friendly narrator.',
    output_modalities: ['audio', 'text'],
    temperature: 0.8,
    audio: {
      input: {
        turn_detection: {
          type: 'semantic_vad',
          create_response: true,
          interrupt_response: true
        }
      },
      output: {
        voice: 'Clive',
        model: 'inworld-tts-1.5-mini',
        speed: 1.0
      }
    }
  }
}));

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Choose a Router or LLM

Set modelId in session.update to select which SmartRouter or LLM handles the conversation. The format is provider/modelName or inworld/routerId: 
ws.send(JSON.stringify({
  type: 'session.update',
  session: {
    modelId: 'openai/gpt-4o-mini'
  }
}));
If you omit modelId, the default model (google-ai-studio/gemini-2.5-flash) is used. You can change the model mid-session with a partial update — the new model takes effect on the next response.

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Choose a Voice

Set audio.output.voice to control the agent’s speaking voice: 
ws.send(JSON.stringify({
  type: 'session.update',
  session: {
    audio: { output: { voice: 'Olivia' } }
  }
}));
The default voice is Dennis. Browse available voices in the TTS Playground or list them programmatically with the List Voices API.

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Choose a TTS Model

Set audio.output.model to select the text-to-speech model: 
ws.send(JSON.stringify({
  type: 'session.update',
  session: {
    audio: { output: { model: 'inworld-tts-1.5-max' } }
  }
}));
ModelSizeNotes
inworld-tts-1.5-mini1BFaster inference, lower latency (default)
inworld-tts-1.5-max8BHigher quality audio
The default is inworld-tts-1.5-mini. You can change the TTS model mid-session alongside voice or independently.

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Send Input

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Audio

There are two ways to send audio input: Method 1: Streaming Audio (Real-time) Use input_audio_buffer.* events for streaming real-time audio from a microphone:
  1. Convert microphone data to PCM16, 24 kHz, mono.
  2. Send chunks via input_audio_buffer.append.
  3. VAD automatically detects speech boundaries and commits the buffer.
Method 2: Pre-recorded Audio Use conversation.item.create with input_audio content type for pre-recorded audio chunks: 
ws.send(JSON.stringify({
  type: 'conversation.item.create',
  item: {
    type: 'message',
    role: 'user',
    content: [{
      type: 'input_audio',
      audio: base64AudioData  // Base64-encoded PCM16 or OPUS
    }]
  }
}));

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Text

Create explicit conversation items for text turns: 
ws.send(JSON.stringify({
  type: 'conversation.item.create',
  item: {
    type: 'message',
    role: 'user',
    content: [{
      type: 'input_text',
      text: 'Give me a two-sentence summary.'
    }]
  }
}));

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Function Calling

The Realtime API supports function calling so your agent can fetch live data or trigger actions mid-conversation. Define functions in session.tools, then handle calls as they arrive.

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1. Register a tool

ws.send(JSON.stringify({
  type: 'session.update',
  session: {
    type: 'realtime',
    tools: [{
      type: 'function',
      name: 'get_horoscope',
      description: 'Get the horoscope for a zodiac sign',
      parameters: {
        type: 'object',
        properties: {
          sign: {
            type: 'string',
            description: 'Zodiac sign, e.g. Aries, Taurus'
          }
        },
        required: ['sign']
      }
    }],
    tool_choice: 'auto'
  }
}));

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2. Handle the function call

When the model decides to call a function, you receive a response.function_call_arguments.done event with the call_id, function name, and serialized arguments. Execute your logic, then return the result: 
ws.on('message', (buffer) => {
  const event = JSON.parse(buffer.toString());

  if (event.type === 'response.function_call_arguments.done') {
    const { call_id, name, arguments: argsJson } = event;
    const args = JSON.parse(argsJson);

    // Run your business logic
    let result;
    if (name === 'get_horoscope') {
      result = fetchHoroscope(args.sign);
    }

    // Send the function result back
    ws.send(JSON.stringify({
      type: 'conversation.item.create',
      item: {
        type: 'function_call_output',
        call_id,
        output: JSON.stringify(result)
      }
    }));

    // Tell the model to continue with the result
    ws.send(JSON.stringify({ type: 'response.create' }));
  }
});

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3. What happens next

After response.create, the model incorporates the function output and continues the conversation — speaking the horoscope aloud (if output_modalities includes audio) or streaming text deltas. The user hears the answer without any gap in the conversation flow. You can register multiple tools and the model will call them as needed. Each call arrives as a separate response.function_call_arguments.done event with its own call_id.

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Manage Conversation State

Use conversation events to keep context lean:
  • conversation.item.retrieve: pull any prior item by ID.
  • conversation.item.delete: remove items that should not remain in context.
  • conversation.item.truncate: drop everything before a cutoff to manage token usage.
Pair these with max_output_tokens and response.cancel to control overall cost (conversation management guide).

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Monitor Errors

Handle error events (with type, code, and param) and implement a reconnection/backoff strategy for transient failures. See the API reference for error event schemas. 
ws.on('message', (buffer) => {
  const event = JSON.parse(buffer.toString());

  if (event.type === 'error') {
    handleError(event.error);
  }
});